Iterative learning for reliable sensor sourcing systems

ABSTRACT

Providing a registry of sensor devices may comprise obtaining a device, determining one or more information types returned by the device, determining one or more communication protocols used by the device for transmitting information, determining one or more encoding schemes used by the device to format the information, adding the device to the registry of sensor devices including at least the one or more information types, the one or more communication protocols and the one or more encoding schemes, and allowing access to the registry of sensor devices.

FIELD

The present application relates generally to computers, and computerapplications, device sensors, and more particularly to iterativelearning for reliable sensor sourcing systems.

BACKGROUND

Although there is a wide spread of Internet devices and connectedsensors, accessing the right devices that fit one's needs and analyzingthe data returned from those devices do not present an easy task. Inaddition, developing a confidence or quality rating for each source ofdata is an important factor in producing refined and reliable analytics.Currently, such appraisals are done either manually or at best throughdeclarative means, such as the specifications for a sensor provided byits manufacturer. Those methods may be insufficient to face thechallenge posed by the current smart big data usage.

BRIEF SUMMARY

A method for providing a registry of sensor devices, in one aspect, maycomprise obtaining a device. The method may also comprise determiningone or more information types returned by the device. The method mayfurther comprise determining one or more communication protocols used bythe device for transmitting information. The method may further comprisedetermining one or more encoding schemes used by the device to formatthe information. The method may also comprise adding the device to theregistry of sensor devices including at least the one or moreinformation types returned by the device, the one or more communicationprotocols and the one or more encoding schemes. The method may furthercomprise allowing access to the registry of sensor devices.

A system for providing a registry of sensor devices, in one aspect, maycomprise a database comprising the registry of sensor devices. A sensorregistry server module may be operable execute on A processor andfurther operable to obtain a device, determine one or more informationtypes returned by the device. The sensor registry server module may befurther operable to determine one or more communication protocols usedby the device for transmitting information. The sensor registry servermodule may be further operable to determine one or more encoding schemesused by the device to format the information. The sensor registry servermodule may be further operable to add the device to the registry ofsensor devices including at least the one or more information types, theone or more communication protocols and the one or more encodingschemes. An application programming interface may allow access to theregistry of sensor devices.

A computer readable storage medium or device storing a program ofinstructions executable by a machine to perform one or more methodsdescribed herein also may be provided.

Further features as well as the structure and operation of variousembodiments are described in detail below with reference to theaccompanying drawings. In the drawings, like reference numbers indicateidentical or functionally similar elements.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 illustrates a network topology showing sensor registry componentsin one embodiment of the present disclosure.

FIG. 2 is a block diagram illustrating a sensor registry server in oneembodiment of the present disclosure.

FIG. 3 is a flow diagram illustrating a logic control flow of a sensorregistry server in one embodiment of the present disclosure.

FIG. 4 is a flow diagram illustrating an addition request handler methodin one embodiment of the present disclosure.

FIG. 5 is a flow diagram illustrating a sensor request handler method inone embodiment of the present disclosure.

FIG. 6 is a flow diagram illustrating a query handler method in oneembodiment of the present disclosure.

FIG. 7 is a flow diagram illustrating an overview of a sensor registrydevice addition method in one embodiment of the present disclosure.

FIG. 8 is a flow diagram illustrating an overview of a sensor registrymethod in one embodiment of the present disclosure.

FIG. 9 is a flow diagram illustrating an overview of a sensor registryclient method in one embodiment of the present disclosure.

FIG. 10 illustrates a schematic of an example computer or processingsystem that may implement a sensor registry system in one embodiment ofthe present disclosure.

DETAILED DESCRIPTION

A system and method are provided in one embodiment of the presentdisclosure for registry service of sensor devices, for querying of thosesensor devices, and determining quality ratings of those sensor devices.

In one aspect, a system and method may provide a quality rating—aQ-factor—to any data source from sensor devices, e.g., non-humandevices: the rating of a given device-based data source determined bycomparing its responses to those of other devices returning equivalentor similar information. This rating can then be stored persistently(e.g., in a database) for later retrieval, both to gauge the accuracy ofthe given device's responses and for historical analysis of the deviceitself.

A source device or sensor is known to a registry of sensors, forexample, as they are added or registered into the registry. The devicemay be known by its type (describing what variable it measures), model(manufacturer and model number) and an individual registration (similarto the International Mobile Station Equipment Identity (IMEI) for mobilephones). In addition, the registry knows (has information about) thelocation a specific sensor at the time of processing. A registry servermay use the data collected by similar sources (type and or model) in thesame location and crosscheck consistency of readings using one or morealgorithms, for example, used in crowd sourcing methodologies. Otheralgorithms may be used.

With the multiplication and accumulation of cross-checks over time, theregistry is enabled to provide a Q-factor related to a model of deviceor even to a specific device. For example, Q-factor values may beassigned as follows: Q-factor will be 0 if not yet fully assessed, 1 forhighly reliable sources, 2 for average reliability, 3 for unreliablesources.

During an analytics process, presence of sources having Q-factor valueof 1 (Q-factor 1 sources) would provide high confidence about theprovide data. Sources having Q-factor value of 2 (Q-factor 2 sources)may be considered in absence of Q-factor 1 sources. Sources havingQ-factor value of 3 (Q-factor 3 sources) may cause a server to generatea reliability warning to a user system.

FIG. 1 illustrates a network topology showing sensor registry componentsin one embodiment of the present disclosure. A sensor registry server110 may obtain information associated with a plurality of sensor devices(e.g., 130, 140, 150, 160), and provide sensor registry services as ismore fully described below, such as storing a registry of sensordevices, determining their quality ratings, and selecting and providingone or more sensor devices that meet the requests of one or more clients(e.g., 170), for instance, via a network 120.

Examples of sensor devices may include but are not limited to one ormore cameras (e.g., those in cell phones), one or more audio/videoand/or other media processing devices, air quality detector or sensor(e.g., carbon dioxide sensor), and other sensor devices.

Sensor sourcing may comprise sourcing or obtaining data or informationfrom a plurality of sensor devices, for example, image processing, whichmay be supervised or unsupervised or combination of supervised orunsupervised processing, such as labeling and classification, of imagesthat may be obtained from sensor devices such as cameras in cell phones.Sensor sourcing may also include media processing, e.g., detectingtraffic and/or road conditions such as near collisions, ice roads, treesnear roads that may fall soon, and/or other condition detected byaudio/video and/or other sensors that might be installed throughout theroads and/or streets in geographic locations. Sensor sourcing may alsoinclude obtaining information about air quality in a city or anotherlocation from a carbon dioxide detector or sensor, which may also beinstalled on locations in the city. Sensor sourcing generally sourcesinformation from sensors or such devices.

Data may be collected from a number of sensors, whose prior knowledge ofreliability is not known. Requests made to those sensors to obtain thedesired information may or may not produce accurate results. The sensorregistry server in one embodiment of the present disclosure may store aregistry of sensors, determine their quality ratings, and also provideto one or more clients those sensors that best produce the resultsneeded by a client (or a requestor requesting sensor information).

FIG. 2 is a block diagram illustrating an example sensor registry serverin one embodiment of the present disclosure, for example, a sensorregistry server shown in FIG. 1 at 110. A sensor registry server mayinclude one or more processors, for example, one or more centralprocessing units that execute the sensor registry service methodologiesas described herein. The sensor registry may comprise other types ofprocessing units. A network interface 210 allows the sensor registryserver to communicate with a variety of devices over a network. Astorage device 220 may store data used and processed by the sensorregistry server, including, for example, the information about aplurality of registered sensors. In another aspect, such information ordata may be stored remotely from the server. A memory device 230 maystore server logic 240, which may comprise an addition request handler250 that handles adding or registering one or more new sensors into thesensor registry service, a sensor request handler 260 that handlesrequests for one or more sensors, a query handler 270 that handlesqueries and a sensor registry server database 290 application thathandles storage and retrieval of data related to sensor devices. Theserver logic 240 may comprise machine or computer executableinstructions.

FIG. 3 is a flow diagram illustrating a logic control flow of a sensorregistry server in one embodiment of the present disclosure. At 300, thelogic waits for input. At 310, it is determined whether the input is arequest to add a sensor. If so, at 320, an addition request handler isinvoked to add or register a new sensor into a sensor registry. Thelogic may then return to 300 to wait for the next input to be received.If at 310, if the input is not an addition request, at 330, it isdetermined whether the input is a request for a sensor. If so, at 340, asensor request handler is invoked to respond to a request for one ormore sensors. The logic may then return to 300 to wait for the nextinput to be received. At 330, if the input is not a sensor request, at350, it is determined whether the input is for a query. If so, at 360, aquery handler is invoked to query one or more sensors for information.The logic may then return to 300 to wait for the next input to bereceived. If the input is not for a query, a miscellaneous handler maybe invoked at 370, for handling the input appropriately.

FIG. 4 is a flow diagram illustrating an addition request handler methodin one embodiment of the present disclosure. The addition requesthandler may acquire information associated with a given sensor that isbeing added to the sensor registry. At 410, the input or sensor additionrequest may be parsed to determine all information types provided by thegiven sensor (e.g., a carbon dioxide sensor provides carbon dioxidelevel in the air, a thermostat provides temperature information, acamera (image sensor) provides image information, etc.). The input maybe also parsed to determine the communication protocol for each datatype (e.g., how the given sensor communicates its sensor data), and theencoding method used for each returned data type. At 420, an entry iscreated for the given sensor in the sensor registry database (e.g., FIG.2 at 290), including the determined information, and stored.

FIG. 5 is a flow diagram illustrating a sensor request handler method inone embodiment of the present disclosure. The sensor request handler inone embodiment responds to requests (e.g., from a client device orapplication) to the sensor registry server for one or more sensordevices, e.g., all sensors returning a given type of data (e.g., carbondioxide level in the air, temperature, traffic information), e.g., thatmatch one or more given constraint such as a location constraint (e.g.,location within 1 mile of location X, or location in city Y, country Z).At 510, the one or more location constraints and one or more data typesbeing requested in the sensor request are determined. For example, therequest message may be parsed to determine the information. At 520, alist of all sensors that provide the requested data type is collectedfrom the sensor registry server database. At 530, each of the sensors inthe list is queried to determine whether the sensor meets the givenconstraint. For example, each of the sensors may be queried, requestingits current location. For example, a message may be sent in real time toeach of the sensors to determine the sensor's current location and/orother information or attributes associated with the sensor. The list ofsensors is then pruned or filtered to only include those sensors thatcurrently fit the specified one or more constraints, e.g., one or morespecified location constraints. At 540, the sensors listed in the prunedor filtered list of sensors is returned to the requestor (e.g., a clientapplication or device). The information returned to the requestor mayinclude not only the list of sensors but also an indication of theaccess protocol and return data format for each of the sensors in thelist of sensors. With such information, the requestor may directlycommunicate with those sensors for the needed or desired informationfrom the sensors. In one embodiment of a method of the presentdisclosure, a reliability factor may be also returned as one of theseveral pieces of data associated with a given returned sensor. Forinstance, in addition to a given request specifying the type andlocation range of desired sensors, the request can also indicate arequested reliability factor (or range of acceptable reliabilityfactors). Then, the method of the present disclosure in one embodimentmay could prune the returned sensor based not only on type and currentlocation, but also based on their reliability factor, returning onlythose which meet or surpass the requested reliability factor thresholdor range.

FIG. 6 is a flow diagram illustrating a query handler method in oneembodiment of the present disclosure. A request for query queries anappropriate set of sensors for information. In one embodiment of thepresent disclosure, a given sensor's Q-factor indicates how well thegiven sensor's reading matches those of the other matching sensorsmaking the same measurement. For example, the Q-factor can beincremented every time the sensor's reading approximates that of theother sensors, while being decremented when it does not. This continualincrementing allows a given high-quality sensor's Q-factor to reflectits superior quality. Once a given sensor has broken down and startsreturning faulty data, e.g., due to age, the continual decrementing ofthe Q-factor corrects even a previously high Q-factor, to reflect thesensor's reduced measurement quality. At 610, one or more constraints(e.g., location constraints) and data types from a given query aredetermined. For example, the query request message may include theinformation regarding the data types (also referred to as informationtypes) and one or more constraints that can be extracted from themessage. At 620, a list or a set of sensors are obtained for the givenquery, for example, using a sensor request handler (e.g., described withreference to FIG. 5). At 630, the sensors in the list are queried, usingrespective communications protocols. The data returned by the sensorsare decoded using a respective encoding method. At 640, given the returnvalues from each of the sensors, the quality and reliability factor(Q-factor) is updated in the sensor registry database for each of thesensors. At 650, the data returned by each of the sensors is returned tothe query requestor, including the identifier (ID) of the sensor andassociated Q-factor.

FIG. 7 is a flow diagram illustrating an overview of a sensor registrydevice addition method in one embodiment of the present disclosure. At702, all information types provided by a given sensor device, e.g.,location awareness, temperature measurement, carbon dioxide measurement,traffic congestion, may be determined. At 704, a data communicationprotocol for communicating with the given sensor device is determinedfor each information or data type. There may be a differentcommunications protocol for each data type. At 706, an encoding methodor standard for the information returned by the give sensor device isdetermined for each type of information. Different types of informationmay use different data encoding method. At 708, a sensor registry iscontacted, if not done already, and a request to add the given sensordevice is posted to the sensor registry. In one embodiment of thepresent disclosure an application programming interface (referred to asa sensor registry service device management API) may be utilized to posta request to the sensor registry. At 710, the sensor registry adds thegiven sensor device along with the list of its information type, thecommunications protocol for each type and the encoding method for eachtype. The processing shown in FIG. 7 may be performed in a distributedmanner. For example, the processing at 702, 704 and 706 may be performedat a different device than the sensor registry server implementing thesensor registry. Hence, for example, the processing at 702, 704 and 706may be performed at a remote device, then the sensor registry servercontacted for adding the given sensor device with the determinedinformation.

FIG. 8 is a flow diagram illustrating an overview of a sensor registrymethod in one embodiment of the present disclosure. At 802, a sensorregistry is accessed. The sensor registry may include a plurality ofsensor devices that are actively being added and deleted from theregistry. At 804, a request is received. The request may include aspecification of desired data type for measuring and one or moreconstraints such as a location constraint. At 806, a list of allcurrently active sensor devices from the sensor registry that can returnthe requested data type is determined. At 808, the list is furtherrefined or filtered to include only those sensor devices that meet thespecified one or more constraints (e.g., location constraint). At 810,the list of sensor devices resulting from the processing at 808 isreturned to the requestor, including for each sensor device in the list,indicia of the access protocol and return data format.

FIG. 9 is a flow diagram illustrating an overview of a sensor registryclient method in one embodiment of the present disclosure. At 902, aclient device or application may contact a sensor registry service andpost a request. The request may include a specification of data type tobe measured and one or more constraints (e.g., location). At 904,response is received from the sensor registry service. The responsecontains a set of sensor devices and associated communication protocoland data encoding method for each sensor device in the set. At 906, theclient device or application may communicate with the device using thespecified access protocol, retrieve a response from the device (e.g.,measured data), and format or decode the response using the specifiedreturned data format specification.

A methodology of the present disclosure may allow for quicklyidentifying which one or more sensors are eligible to provide theexpected data and how to access those one or more sensors for theexpected data. For example, there may be number of sensor devices thatdetect and convey information. However, those sensor devices could be inmotion, e.g., embedded or installed in a moving vehicle such as a car ora bus. Those sensors also could be currently unavailable (e.g., turnedoff or not ready for data collection). They also could not be located inthe desired spatial location. They may not also collect the right typeof data (carbon dioxide level in the air, carbon monoxide level in theair, and/or other types of data or information). In addition, differentsensor devices may operate with different data formatting protocols,variable specifications and heterogeneous connectivity. An embodiment ofthe present disclosure may maintain a registry of sensors and identifythose that provide the desired data at any one time, e.g., which one ormore sensors to access to get the right data according to sensorcharacteristics and availability. Multitude of sensors, which may bepresent in a dynamic world of sensors, are managed in a sensor registry,for instance, in terms of volume, localization, availability andcharacteristics, and a user is enabled to access the right one(s) thatmeet the user's criteria.

Consider for example, a scenario in which it is desired to map carbondioxide concentration or amount in the air in a geographical area. Arequestor may interrogate a sensor registry server and ask for availablecarbon dioxide sensor device in the given area. The sensor registryserver may determine a set of sensors that meet the requestor'scriteria, e.g., those that detect carbon dioxide levels and are locatedin the given geographical area. The sensor registry server may returnthe list of sensor to the requestor along with the associatedcommunication protocol and data encoding format. In this way, therequestor may directly query the returned sensors for the information.In another aspect, the sensor registry server may query the list ofsensors, and return the information to the requestor. Yet in anotheraspect, the sensor registry server may redirect the query to thoseidentified sensors while providing the specification associated witheach of the sensors to the requestor. The readings may be sent in RAWmode to the requester who then reformats them to the appropriate formatby applying a translation method based on the received specifications.

A system and method of the present disclosure in one embodiment mayallow for facilitating the federation of heterogeneous devices, e.g., inthe absence of a true standard, which may be used as the standard. Inone embodiment, the server of the present disclosure may register everypossible device, e.g., in response to a request by a requestor. Arequestor may be a producer or manufacturer of the device or a user ofthe device, or another. A device may be registered with the server ofthe present disclosure, and an entry in the server (e.g., server'sdatabase) may include the following information:

-   -   Device identification (e.g., a media access control address (MAC        address));    -   Device type: sensor—connected device (refrigerator—air        conditioner (A/C)), e.g., one particular sensor which measures        temperature that is integrated into a refrigerator to control        the cooling system would have a device type of “refrigerator,”        while another temperature measuring sensor used in an automobile        to provide a display of the current engine temperature would        have a device type of “automobile”;    -   Device subtype (barometric (BP) sensor—carbon dioxide (CO2)        sensor, etc.), e.g., other sensor devices within the device;    -   Description of the data format produced by the sensor;    -   Interval of confidence and precision of the sensor (e.g., like        in a scientific measurement device);    -   Addition entry field for additional characteristics to be added        now or in the future.

In one embodiment, this information may be created by the deviceproducer. Geo-location information may be input based on the location ofthe device detected.

Occurrence of errors may be common in a sensor sourcing system wheretasks (requests for detecting information) are distributed ortransmitted to multiple sensor devices (e.g., unidentified sensors). Forexample, some sensors might not be available, some sensors might not beidentifiable, sensor crowd may be large (abundance of information, whichmay or may not be accurate), there may be no prior knowledge of thesensor's reliability, tasks may be distributed through open calls (noparticular standard), there is no ability to condition rewards oncorrectness of sensor analyses and/or responses. For example, in asensor sourcing system, batches of tasks may be distributed(electronically) to unidentified group of sensor, e.g., throughbroadcast for information. However, these “information piece-sensors”may provide possibly inaccurate data because, e.g., sensors may makerandom errors based on their own quality. To overcome such errors, atask may be assigned to multiple sensors. The final result may be anaggregation of multiple sensors' response for each task. For instance,estimation is performed after all the answers are obtained and theaccuracy of information from different sensors may be based on thenumber of similar response from the sensors.

Because the information sensors provide can be unreliable, a sensorsourcer would need to devise one or more schemes to increase confidencein the data the sensors produce, e.g., by assigning each task multipletimes and combining the answers in some way such as majority voting. Inone embodiment, a method of the present disclosure may provide forachieving a level of reliability in responses from sensors, e.g., withminimum cost. In one embodiment of the present disclosure, a generalmodel of such sensor sourcing tasks is considered. In one embodiment,the model is formulated as a problem of minimizing the total price(i.e., number of task assignments) that is to be paid to achieve atarget overall reliability.

An embodiment of the method of the present disclosure may use analgorithm for deciding which tasks to assign to which sensors and forinferring correct answers from the sensors' replies. This algorithm mayoutperform majority voting and is asymptotically optimal throughcomparison to an oracle that knows the reliability of every sensor.

The problem may include several characteristics of sensor sourcingsystem: sensor devices are neither persistent nor identifiable; eachbatch of tasks is solved by a sensor device that may be completely newand that may be never seen again. Thus one cannot identify and reuseparticularly reliable sensors. Nonetheless, by comparing one sensordevice's answer to others' on the same question, it is possible to drawconclusions about a sensor's reliability, which can be used to weightheir answers to other questions in their batch.

Unlike many inference problems which make inferences based on a fixedset of signals, an algorithm used in the present disclosure can choosewhich signals to measure by deciding which questions to ask whichsensors. The algorithm may assign tasks according to random regularbipartite graph schema, and the inference is based on an iterativealgorithm.

Such algorithm may take the form of one used in crowd souring, butrespect to sensors. A crowd sourcing algorithm is described in“Iterative Learning for Reliable Crowdsourcing Systems” by David R.Karger, Sewoong Oh, and Devavrat Shah, Department of ElectricalEngineering and Computer Science, Massachusetts Institute of Technology,Cambridge, Mass. 02139. Portions of that disclosure are reiteratedherein below as applied to sensors in the present disclosure. A crowdsourcing model may comprise a set of m tasks {t_(i)} where i is anelement of m (i∈[m]). Each task may be associated with an unobserved“correct” response, si∈{±1}. Tasks are assigned to n sensors from thenetwork of sensors (“sensor crowd”), {w_(j)} where j∈[n]. When a task isassigned a sensor, the sensor possibly may produce an inaccurateresponse. Answer on task from a sensor may be annotated as A_(ij)∈{±1}.The model may capture the diversity in sensor response reliability. Eachsensor w_(j) may be characterized by reliability p_(j)∈[0, 1]. Eachsensor may make random errors in responding to a request. If a taskt_(i) is assigned to a sensor w_(j) then,

$A_{ij} = \left\{ {\begin{matrix}{s_{i}\mspace{14mu}{with}\mspace{14mu}{probability}\mspace{14mu} p_{j}} \\{{{- s_{i}}\mspace{14mu}{with}\mspace{14mu}{probability}\mspace{14mu} 1} - p_{j}}\end{matrix},{{{and}A_{ij}} = {0\mspace{14mu}{if}\mspace{14mu} t_{i}\mspace{14mu}{is}\mspace{14mu}{not}\mspace{14mu}{assigned}\mspace{14mu}{to}\mspace{14mu} w_{j}A_{ij}\mspace{14mu}{is}\mspace{14mu}{independent}\mspace{14mu}{of}\mspace{14mu}{any}\mspace{14mu}{other}\mspace{14mu}{event}\mspace{14mu}{given}\mspace{14mu}{p_{j}.}}}} \right.$

In one embodiment of the present disclosure, it may be further assumedthat the reliability of sensors {p_(j)} where j∈[n] are independent andidentically distributed random variables with a given distribution on[0, 1]. One example is spammer-hammer model where each sensor is eithera “hammer” with probability q or is a “spammer” with probability 1−q. Ahammer answers all questions correctly, in which case p_(j)=1, and aspammer gives random answers, in which case p_(j)=½. Given this randomvariable p_(j), a parameter is defined q∈[0, 1], which captures the“average quality” of the crowd: q≡E[(2p_(j)−1)²], where E is functionthat returns an estimate of the overall quality of the results returnedin response to each task.

A value of q close to 1 indicates that a large proportion of the workersare diligent, whereas q close to 0 indicates that there are manyspammers in the crowd. However, q may be necessary to determine how manytimes a task should be replicated and how many iterations need to be runto achieve a level of reliability.

In one embodiment of a sensor sourcing model in the present disclosure,a taskmaster first decides which tasks should be assigned to whichsensors, and then estimates the correct solutions {S_(i)} where i∈[m]once all the answers {A_(ij)} are submitted. In a one-shot scenario, forexample, in one embodiment, an inference algorithm of the presentdisclosure may utilize bipartite graph schema, in which all questionsare asked simultaneously and then an estimation is performed after allthe answers are obtained. Assigning tasks to nodes may involve designinga bipartite graph G({t_(i)} where i∈[m]∪{w_(j)} where j∈[n], E) with mtask and n sensor nodes, and E (different from above) being the set ofall (task, reply) pairs Each edge (i, j) indicates that task t_(i) wasassigned to sensor w_(j).

The iterative algorithm may operate on real-valued task messages{x_(i→j)}_((i,j)∈E) and sensor messages {y_(j→i)}_((i,j)∈E). The sensormessages may be initialized as independent Gaussian random variables. Ateach iteration, the messages may be updated according to an update rule,where δ_(i) is the neighborhood of t_(i). A sensor message {y_(j→i)}represents a belief on how “reliable” the sensor j is, such that thefinal estimate is a weighted sum of the answers weighted by eachsensor's reliability: ŝ=sign(Σ_(j∈δ) _(i) A_(ij)y_(j→i)).

For random (l, r)-regular bipartite graph based task assignments withthe iterative inference algorithm, the probability of error decaysexponentially in lq, up to a universal constant and for a broad range ofthe parameters l, r and q. With a reasonable choice of l=r and bothscaling like (1/q) log (1/ε), the proposed algorithm achieves error lessthan ε for any ε∈(0, ½).

Message passing in the iterative algorithm is represented as taskmessage: {x_(i→j)}_((i,j)∈E), and sensor message: {y_(j→i)}_((i,j)∈E),which also represents sensor j's reliability on item i. Line 2 of thealgorithm represents an update process: x_(i→j) ^((k))←Σ_(j′∈δ) _(i)_(\j)A_(ij′)y_(j′→i) ^((k−1)) computes the item likelihood to bepositive. Tasks are more likely to be positive if reliable sensors sayit is positive. y_(j→i) ^((k))←Σ_(i′∈δ) _(j) _(\i)A_(i′j)x_(i′→j)^((k−1)) computes the reliability of users. Again, the above crowdsourcing algorithm, described in detail in “Iterative Learning forReliable Crowdsourcing Systems” by David R. Karger, Sewoong Oh, andDevavrat Shah, Department of Electrical Engineering and ComputerScience, Massachusetts Institute of Technology, Cambridge, Mass. 02139,provides another example method that can be used for calculating andupdating sensors' quality factors, e.g., described with reference toFIG. 6.

FIG. 10 illustrates a schematic of an example computer or processingsystem that may implement a sensor registry system in one embodiment ofthe present disclosure. The computer system is only one example of asuitable processing system and is not intended to suggest any limitationas to the scope of use or functionality of embodiments of themethodology described herein. The processing system shown may beoperational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with the processing system shown in FIG. 10 mayinclude, but are not limited to, personal computer systems, servercomputer systems, thin clients, thick clients, handheld or laptopdevices, multiprocessor systems, microprocessor-based systems, set topboxes, programmable consumer electronics, network PCs, minicomputersystems, mainframe computer systems, and distributed cloud computingenvironments that include any of the above systems or devices, and thelike.

The computer system may be described in the general context of computersystem executable instructions, such as program modules, being executedby a computer system. Generally, program modules may include routines,programs, objects, components, logic, data structures, and so on thatperform particular tasks or implement particular abstract data types.The computer system may be practiced in distributed cloud computingenvironments where tasks are performed by remote processing devices thatare linked through a communications network. In a distributed cloudcomputing environment, program modules may be located in both local andremote computer system storage media including memory storage devices.

The components of computer system may include, but are not limited to,one or more processors or processing units 12, a system memory 16, and abus 14 that couples various system components including system memory 16to processor 12. The processor 12 may include a sensor registry servicemodule 10 that performs the methods described herein. The module 10 maybe programmed into the integrated circuits of the processor 12, orloaded from memory 16, storage device 18, or network 24 or combinationsthereof.

Bus 14 may represent one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Computer system may include a variety of computer system readable media.Such media may be any available media that is accessible by computersystem, and it may include both volatile and non-volatile media,removable and non-removable media.

System memory 16 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) and/or cachememory or others. Computer system may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 18 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(e.g., a “hard drive”). Although not shown, a magnetic disk drive forreading from and writing to a removable, non-volatile magnetic disk(e.g., a “floppy disk”), and an optical disk drive for reading from orwriting to a removable, non-volatile optical disk such as a CD-ROM,DVD-ROM or other optical media can be provided. In such instances, eachcan be connected to bus 14 by one or more data media interfaces.

Computer system may also communicate with one or more external devices26 such as a keyboard, a pointing device, a display 28, etc.; one ormore devices that enable a user to interact with computer system; and/orany devices (e.g., network card, modem, etc.) that enable computersystem to communicate with one or more other computing devices. Suchcommunication can occur via Input/Output (I/O) interfaces 20.

Still yet, computer system can communicate with one or more networks 24such as a local area network (LAN), a general wide area network (WAN),and/or a public network (e.g., the Internet) via network adapter 22. Asdepicted, network adapter 22 communicates with the other components ofcomputer system via bus 14. It should be understood that although notshown, other hardware and/or software components could be used inconjunction with computer system. Examples include, but are not limitedto: microcode, device drivers, redundant processing units, external diskdrive arrays, RAID systems, tape drives, and data archival storagesystems, etc.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: a portable computerdiskette, a hard disk, a random access memory (RAM), a read-only memory(ROM), an erasable programmable read-only memory (EPROM or Flashmemory), a portable compact disc read-only memory (CD-ROM), an opticalstorage device, a magnetic storage device, or any suitable combinationof the foregoing. In the context of this document, a computer readablestorage medium may be any tangible medium that can contain, or store aprogram for use by or in connection with an instruction executionsystem, apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages, a scripting language such as Perl, VBS or similarlanguages, and/or functional languages such as Lisp and ML andlogic-oriented languages such as Prolog. The program code may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider).

Aspects of the present invention are described with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

The computer program product may comprise all the respective featuresenabling the implementation of the methodology described herein, andwhich—when loaded in a computer system—is able to carry out the methods.Computer program, software program, program, or software, in the presentcontext means any expression, in any language, code or notation, of aset of instructions intended to cause a system having an informationprocessing capability to perform a particular function either directlyor after either or both of the following: (a) conversion to anotherlanguage, code or notation; and/or (b) reproduction in a differentmaterial form.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements, if any, in the claims below areintended to include any structure, material, or act for performing thefunction in combination with other claimed elements as specificallyclaimed. The description of the present invention has been presented forpurposes of illustration and description, but is not intended to beexhaustive or limited to the invention in the form disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the invention.The embodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

Various aspects of the present disclosure may be embodied as a program,software, or computer instructions embodied in a computer or machineusable or readable medium, which causes the computer or machine toperform the steps of the method when executed on the computer,processor, and/or machine. A program storage device readable by amachine, tangibly embodying a program of instructions executable by themachine to perform various functionalities and methods described in thepresent disclosure is also provided.

The system and method of the present disclosure may be implemented andrun on a general-purpose computer or special-purpose computer system.The terms “computer system” and “computer network” as may be used in thepresent application may include a variety of combinations of fixedand/or portable computer hardware, software, peripherals, and storagedevices. The computer system may include a plurality of individualcomponents that are networked or otherwise linked to performcollaboratively, or may include one or more stand-alone components. Thehardware and software components of the computer system of the presentapplication may include and may be included within fixed and portabledevices such as desktop, laptop, and/or server. A module may be acomponent of a device, software, program, or system that implements some“functionality”, which can be embodied as software, hardware, firmware,electronic circuitry, or etc.

The embodiments described above are illustrative examples and it shouldnot be construed that the present invention is limited to theseparticular embodiments. Thus, various changes and modifications may beeffected by one skilled in the art without departing from the spirit orscope of the invention as defined in the appended claims.

We claim:
 1. A method for providing a registry of sensor devices,comprising: receiving an addition request from a device, the additionrequest comprising at least an information type returned by the device,a communication protocol used by the device for transmitting informationassociated with the information type, and an encoding scheme used by thedevice to format the information; adding the device to the registry ofsensor devices including at least the information type returned by thedevice, the communication protocol and the encoding scheme; allowingaccess to the registry of sensor devices; transmitting, by a processorvia a network, a request for information to a set of sensor devicesregistered in the registry of sensor devices that make same type ofmeasurement requested in the information, using respective sensordevice's communications protocols specified in the registry of sensordevices; receiving, by the processor, the information from the set ofsensor devices; and updating in the registry of sensor devices, by theprocessor, a reliability factor of a sensor device in the set of sensordevices based on the information comprising measurements received fromthe set of sensor devices, the reliability factor indicating an accuracyof measurement data provided by the sensor device, the reliabilityfactor of a sensor device incremented responsive to determining themeasurement data provided by the sensor device matches to a degreesensor data provided by other sensor devices providing the samemeasurement type, the reliability factor of the sensor devicedecremented responsive to determining the measurement data does notmatch to the degree the sensor data provided by the other sensor devicesproviding the same measurement type; and assigning a reliability factorvalue to the sensor device, wherein a model type indicating manufacturerand model number of the sensor device is identified and the reliabilityfactor value is assigned to other sensor devices having the same modeltype.
 2. The method of claim 1, further comprising providing anapplication programming interface for interfacing with the registry ofsensor devices for the information.
 3. The method of claim 1, whereinthe method is performed for a plurality of heterogeneous devices.
 4. Themethod of claim 1, wherein the allowing access comprises: receiving arequest from a requestor for a device that provide a specified type ofinformation; determining a list of devices in the registry of sensorsthat provide the specified type of information; and returning the listof devices to the requestor.
 5. The method of claim 4, wherein thereturning further comprises returning the list of devices with at leastthe communication protocol and the encoding scheme associated with eachof the devices in the list.
 6. The method of claim 4, wherein therequest further comprises a constraint associated with the devicerequested, and the determining the list of devices in the registry ofsensors further comprises selecting at least one device in the registrythat satisfy the constraint.
 7. The method of claim 6, wherein theconstraint comprises at least one location constraint, and the list ofdevices in the registry of sensors are queried in real-time to determinecurrent location of each of the devices to determine at least oneconstraint that satisfies the at least one location constraint.
 8. Themethod of claim 1, the reliability factor value comprising one of: notfully assessed; highly reliable, average reliable, and unreliable.